US7953143B2ActiveUtilityPatentIndex 51
Systems and methods for deriving parameters for impulse noise detectors
Est. expiryFeb 22, 2028(~1.6 yrs left)· nominal 20-yr term from priority
H04L 27/2647
51
PatentIndex Score
1
Cited by
17
References
34
Claims
Abstract
A system is described that comprises a frequency domain impulse noise detector configured to monitor received discrete multi-tone (DMT) symbols for impulse noise, a Reed Solomon (RS) decoder with erasure and erasure correction capability for performing error correction on received DMT symbols, and an optimization module configured to adjust parameters associated with the impulse noise detector, the optimization module configured to adjust values for β pivot , β c , and a ratio (m/M), wherein M is a number of monitored tones, m is a number of slicer error samples that must exceed a decision threshold for a symbol to be flagged as corrupted, and β pivot and β c are values associated with a monotonic function of a ratio of a statistical parameter of disruptive noise to a statistical parameter of nominal noise.
Claims
exact text as granted — not AI-modified1. A method comprising:
setting, by a processor, values for β pivot , β c , and a ratio (m/M), wherein M is a number of monitored tones, m is a number of slicer error samples that must exceed a decision threshold for a symbol to be flagged as corrupted, and β pivot and β c are values associated with a monotonic function of a ratio of a statistical parameter of disruptive noise to a statistical parameter of nominal noise;
selecting a plurality of values for M and computing a corresponding value of m based on the ratio (m/M);
calculating α based on the values of M, m, and β pivot , wherein α is a tunable scaling factor;
calculating a probability of a miss and a probability of a false alarm based on the values of M, m, β c , and α for each value of M; and
adjusting the value of M such that the larger of the probability of a miss and the probability of a false alarm is a predetermined scale factor less than a predetermined bit error rate (BER) at a selected value of β c in order to achieve the predetermined BER.
2. The method of claim 1 , wherein setting the pivot value β pivot comprises setting β pivot to a value within a predetermined range of a noise margin associated with transmission of a tone.
3. The method of claim 1 , wherein the predetermined BER threshold is 10 −7 .
4. The method of claim 1 , wherein the predetermined scale factor is 10 −2 .
5. The method of claim 1 , wherein adjusting the value of M comprises increasing or decreasing the number of monitored tones M and the value of m according to the ratio (m/M) such that a different value for β c can be incorporated for detection of corrupted symbols.
6. The method of claim 1 , wherein the statistical parameter is standard deviation and wherein the monotonic function is the identity function.
7. The method of claim 1 , wherein calculating α is based on the equation β=g(β pivot , M, m) where g( ) denotes a function of β pivot , M, and m.
8. The method of claim 7 , wherein
g
(
β
pivot
,
M
,
m
)
=
β
pivot
2
ln
(
M
m
)
.
9. A system comprising:
a frequency domain impulse noise detector configured to monitor received discrete multi-tone (DMT) symbols for impulse noise;
a Reed Solomon (RS) decoder with erasure and erasure correction capability for performing error correction on received DMT symbols; and
an optimization module configured to adjust parameters associated with the impulse noise detector, the optimization module configured to adjust values for β pivot , β c , and a ratio (m/M), wherein M is a number of monitored tones, m is a number of slicer error samples that must exceed a decision threshold for a symbol to be flagged as corrupted, and β pivot and β c are values associated with a monotonic function of a ratio of a statistical parameter of disruptive noise to a statistical parameter of nominal noise.
10. The system of claim 9 , wherein the optimization module is further configured to adjust the pivot value β pivot to a value within a predetermined range of a noise margin associated with transmission of a tone.
11. The system of claim 9 , wherein the system comprises an xDSL modem.
12. The system of claim 9 , wherein the statistical parameter is standard deviation and wherein the monotonic function is the identity function.
13. The system of claim 9 , wherein the optimization module is further configured to select a plurality of values for M and compute a corresponding value of m based on the ratio (m/M); calculate a based on the equation α=g(β pivot , M, m), where g( ) denotes a function of β pivot , M, and m, wherein α is a tunable scaling factor; and calculate a probability of a miss and a probability of a false alarm based on the values of M, m, β c , and α for each value of M.
14. The system of claim 13 , wherein
g
(
β
pivot
,
M
,
m
)
=
β
pivot
2
ln
(
M
m
)
.
15. The system of claim 9 , wherein the optimization module is further configured to adjust the value of M such that the larger of the probability of a miss and the probability of a false alarm is a predetermined scale factor less than a predetermined bit error rate (BER) at a selected value of β c in order to achieve the predetermined BER.
16. The system of claim 15 , wherein the predetermined ER is 10 −7 .
17. The system of claim 15 , wherein the predetermined scale factor is 10 −2 .
18. A method comprising:
setting, by a processor, values for β pivot and β c , wherein β pivot and β c are values associated with a monotonic function of a ratio of a statistical parameter of disruptive noise to a statistical parameter of nominal noise;
selecting a fixed ratio (m/M), wherein M is a number of monitored tones and wherein m is a number of slicer error samples that must exceed a decision threshold for a symbol to be flagged as corrupted;
selecting a plurality of values for M and computing a corresponding value of m based on the fixed ratio (m/M);
calculating a based on the values of M, m, and β pivot , wherein α is a tunable scaling factor; and
calculating a probability of a miss and a probability of a false alarm based on the values of M, m, β c , and a for each of the plurality of values of M.
19. The method of claim 18 , further comprising selecting from among the plurality of values for M such that the larger of the probability of a miss and the probability of a false alarm is a predetermined scale factor less than a predetermined bit error rate (BER) at a selected value of β c in order to achieve the predetermined BER.
20. The method of claim 18 , wherein calculating a comprises calculating α based on the equation α=g(β pivot , M, m) wherein
g
(
β
pivot
,
M
,
m
)
=
β
pivot
2
ln
(
M
m
)
.
21. The method of claim 18 , wherein the predetermined BER is 10 −7 .
22. The method of claim 18 , wherein the predetermined scale factor is 10 −2 .
23. The method of claim 18 , further comprising increasing or decreasing the number of monitored tones M and the value of m according to the fixed ratio (m/M) such that a different value for β c can be incorporated for detection of corrupted tones.
24. The method of claim 18 , wherein adjusting a decision threshold comprises selecting a pivot value β pivot such that the value of β pivot is within a predetermined range of a noise margin associated with transmission of a tone.
25. The method of claim 18 , wherein the statistical parameter is standard deviation and wherein the monotonic function is the identity function.
26. A system comprising:
means for monitoring received discrete multi-tone (DMT) symbols for impulse noise;
means for performing error correction on received DMT symbols; and
means for adjusting parameters associated with the impulse noise detector, the adjusting means further configured to adjust values for β pivot , β c , and a ratio (m/M), wherein M is a number of monitored tones, m is a number of slicer error samples that must exceed a decision threshold for a symbol to be flagged as corrupted, and β pivot and β c are values associated with a monotonic function of a ratio of a statistical parameter of disruptive noise to a statistical parameter of nominal noise.
27. The system of claim 26 , wherein the means for adjusting is further configured to adjust the pivot value β pivot to a value within a predetermined range of a noise margin associated with transmission of a tone.
28. The system of claim 26 , wherein the xDSL communications system comprises an xDSL modem.
29. The system of claim 26 , wherein the statistical parameter is standard deviation and wherein the monotonic function is the identity function.
30. The system of claim 26 , wherein the means for adjusting is further configured to select a plurality of values for M and compute a corresponding value of m based on the ratio (m/M); calculate a based on the equation α=g(β pivot , M, m) where g( ) denotes a function of β pivot , M, and m, wherein α is a tunable scaling factor; and calculate a probability of a miss and a probability of a false alarm based on the values of M, m, β c , and a for each value of M.
31. The system of claim 30 , wherein
g
(
β
pivot
,
M
,
m
)
=
β
pivot
2
ln
(
M
m
)
.
32. The system of claim 26 , wherein the means for adjusting is further configured to adjust the value of M such that the larger of the probability of a miss and the probability of a false alarm is a predetermined scale factor less than a predetermined bit error rate (BER) at a selected value of β c in order to achieve the predetermined BER.
33. The system of claim 32 , wherein the predetermined BER is 10 −7 .
34. The system of claim 32 , wherein the predetermined scale factor is 10 −2 .Cited by (0)
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